AI Document Annotation System for Review Feedback Consolidation
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Solution Overview
Problem
Current methods for document review meetings face challenges in accurately capturing and consolidating feedback and suggested edits from participants, as they often rely on manual note-taking and handwritten comments, which can lead to inconsistencies and inefficiencies in incorporating feedback into the original document.
Innovation Solution
An apparatus and method utilizing artificial intelligence to identify and generate annotations for content suggestions from various sources, including physical and electronic documents, and media content, allowing for automatic recognition and integration of feedback into the document, enabling efficient correlation and display of suggested edits within a digital interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual note-taking and handwritten comments are used to capture feedback during document review meetings, then participants can provide suggestions, but the accuracy and consistency of capturing and consolidating feedback deteriorates
Solution Approach 1:
The patent replaces manual mechanical note-taking and handwritten comments with an automated electronic system using optical character recognition (OCR), image processing, and natural language processing to capture, recognize, and consolidate feedback from various sources including handwritten notes, printed comments, and digital annotations, thereby maintaining ease of operation while significantly improving accuracy and consistency
Solution Approach 2:
The patent introduces an intermediary automated processing system that acts as a mediator between participants providing feedback and the document revision process. This intermediary system captures feedback from multiple sources, processes it through OCR and image recognition, and consolidates it into a unified format, ensuring accurate and consistent capture without requiring participants to change their natural feedback-providing behavior
2Quantity of substance
If multiple sources of feedback are collected during document review, then comprehensive input is obtained, but the complexity of consolidating and correlating suggestions increases
Solution Approach 1:
The patent segments the complex consolidation process into distinct automated stages: capturing feedback from multiple sources, processing each source type through appropriate recognition algorithms (OCR for printed text, image processing for handwritten notes), extracting structured data, and consolidating into a unified format. This segmentation reduces overall complexity by making each step manageable and automated
Solution Approach 2:
The patent creates a universal multi-functional processing system that can handle various types of feedback sources (handwritten notes, printed comments, digital annotations) through a single integrated platform. The system uses multiple recognition algorithms and processing methods within one unified architecture, reducing the need for separate systems for each feedback type and thereby reducing overall complexity
3Productivity
If automated processing is used to identify and integrate feedback, then efficiency of document review improves, but the complexity of the processing system increases
Solution Approach 1:
The patent implements a self-service automated processing system that autonomously captures, processes, and consolidates feedback without requiring manual intervention. The system automatically identifies feedback sources, applies appropriate recognition algorithms, extracts relevant information, and integrates suggestions into the document revision process, thereby improving efficiency while managing complexity through automation
Solution Approach 2:
The patent incorporates feedback loops where the processed information is continuously refined and validated. The system uses recognition results to improve subsequent processing, validates extracted data against expected formats, and allows for iterative refinement of the consolidation process, thereby improving efficiency while managing complexity through controlled feedback mechanisms
Data Source
AI summary
Artificial intelligence is introduced into document review to identify content suggestions from input to generate suggested annotations for the reviewed document. An approach is provided for receiving an electronic document that contains original content from an original electronic document for review and electronic mark-ups provided by a first user. One or more electronic mark-ups that represent content suggestions proposed by the first user are identified from the electronic document. For each electronic mark-up of the one or more electronic mark-ups identified a document portion of the original content that corresponds to the electronic mark-up is identified, and an annotation is generated for the electronic mark-up comprising the electronic mark-up and a first user ID for the first user and associating the annotation to the document portion identified. The original content with one or more annotations generated from the one or more electronic mark-ups is displayed, in electronic form, within a display window.